JP7186458B2 - MONITORING DEVICE, MONITORING METHOD, AND PROGRAM - Google Patents

Description

The present invention relates to a monitoring device, monitoring method, program, and body contact member .

An electrical impedance tomography (hereinafter simply referred to as EIT) measurement device applies a weak current from a pair of electrodes attached to the body surface, and from the potential difference generated on the body surface, the conductivity distribution or conductivity in the body It is a technique for imaging the distribution of changes. EIT (Electrical Impedance Tomography) can acquire tomographic images simply by applying a weak electric current, so compared to X-ray CT (Computed Tomography), there is no exposure problem, miniaturization, long-time measurement, and real-time measurement are possible. It has the advantage of being easy.

EIT measurement uses, for example, a plurality of electrodes. These electrodes are brought into contact with the periphery of the site to be measured, and signal cables individually connected to the electrodes are routed and connected to the measuring circuit.

As a related technology, Patent Literature 1 discloses an EIT measurement device that combines EIT technology and technology for estimating the contour and shape of a body.

WO2015/002210

By the way, there is a demand for further technical development in applications for grasping the condition of the body such as the human body.

SUMMARY OF THE INVENTION Accordingly, an object of the present invention is to provide a monitoring device, a monitoring method, a program, and a body contact member that can solve the above-described problems.

According to the first aspect of the present invention, the driver monitoring device is electrically connected to the curvature sensor of the seat belt provided with a plurality of curvature sensors, and the curvature data obtained through the curvature sensor is a shape estimating unit that estimates the shape of the seat belt based on the shape of the seat belt; and a state determination unit that determines the state of the driver based on the shape of the seat belt.

In the driver monitoring device described above, the state determination unit estimates a range in which the seat belt contacts the driver, and drives the curvature sensor located in the contact range.

In the driver monitoring device described above, the condition determination unit determines whether the condition of the driver is normal or abnormal using one or more of the shape of the seat belt, the heart rate, and the ventilation condition.

In the above-described driver monitoring device, the seat belt is electrically connected to the electrodes of the seat belt provided with a plurality of electrodes, and the state determination unit energizes the plurality of electrodes and controls the electrodes. A tomographic image of the driver in the range where the seat belt contacts the driver is generated based on the voltage signal generated during and the driver's condition is determined based on the tomographic image.

In the driver monitoring device described above, the state determination unit detects the heart rate of the driver based on the voltage signals generated between the electrodes and the energization of the electrodes.

In the driver monitoring device described above, the state determination unit detects the ventilation state of the driver based on the voltage signals generated between the electrodes and the energization of the plurality of electrodes.

The driver monitoring device described above further includes a recording unit that records one or more of the tomographic image, the heart rate, the ventilation state, and the driver's state.

The driver monitoring apparatus described above further includes a display processing unit that displays one or more of the tomographic image, the heart rate, the ventilation state, and the driver's state on a monitor.

In the driver monitoring device described above, the state determination unit activates the warning sensor when it determines that the state of the driver is abnormal.

The driver monitoring device described above further includes a correction unit that corrects the output information of the curvature sensor based on the shape of the seat belt when the seat belt is in a predetermined state in which the seat belt is not in use.

Further, according to the second aspect of the present invention, the driver monitoring device is electrically connected to the electrodes of the seat belt provided with a plurality of electrodes, and energizes the plurality of electrodes and the electrodes. a state determination unit that generates a tomographic image of the driver in the range where the seat belt contacts the driver based on the voltage signal generated between the seat belts and determines the state of the driver based on the tomographic image. .

Further, according to the third aspect of the present invention, the monitoring device is connected to a body contact member provided with a plurality of electrodes, and based on electrical signals obtained from the electrodes, a tomographic image and a heart rate of the subject are detected. a state determination unit that calculates state information of one or more of the number and ventilation state, and determines whether the subject's state is normal or abnormal using the state information.

Further, according to the fourth aspect of the present invention, the monitoring device is connected to a body contact member provided with a plurality of curvature sensors, and measures the body movement of the subject based on the signals obtained from the curvature sensors. a state determination unit that calculates state information of one or more of a heart rate and a ventilation state, and determines the state of the subject using the state information.

Further, according to the fifth aspect of the present invention, the monitoring method is such that a monitoring device connected to a body contact member provided with a plurality of electrodes controls a subject to be measured based on electrical signals obtained from the electrodes. Any one or a plurality of state information of a tomographic image, a heart rate, and a ventilation state is calculated, and whether the subject's state is normal or abnormal is determined using the state information.

According to a sixth aspect of the present invention, a monitoring method is provided in which a monitoring device connected to a body contact member provided with a plurality of curvature sensors controls a subject to be measured based on signals obtained from the curvature sensors. one or a plurality of state information of the body motion, heart rate, and ventilation state of the subject, and determine the state of the subject using the state information.

Further, according to the seventh aspect of the present invention, the program causes the computer of the monitoring device connected to the body contact member provided with a plurality of electrodes to cause the subject to be measured based on the electrical signals obtained from the electrodes. tomographic image, heart rate, ventilation state, or a plurality of state information, and using the state information to function as state determination means for determining whether the subject's state is normal or abnormal.

According to the eighth aspect of the present invention, the program causes the computer of the monitoring device connected to the body contact member provided with a plurality of curvature sensors to be measured based on the signals obtained from the curvature sensors. Any one or a plurality of state information of body motion, heart rate, and ventilation state of the person is calculated, and the state information is used to function as state determination means for determining the state of the person to be measured.

According to a ninth aspect of the present invention, a seat belt includes a plurality of periodically arranged electrodes and a plurality of curvature sensors periodically arranged in parallel with the plurality of electrodes.

Further, according to the present invention, the seat belt described above includes an output unit that detects use of the seat belt and outputs a use detection signal to the driver monitoring device.

ADVANTAGE OF THE INVENTION According to this invention, the state of a to-be-measured person's body can be grasped more easily.

It is a figure which shows the driver monitoring device and seat belt by 1st Embodiment. FIG. 2 is a first diagram showing the internal configuration of the seat belt according to the first embodiment; FIG. 1 is a diagram showing a functional configuration of a driver monitoring device according to a first embodiment; FIG. It is a figure explaining the structure of the seatbelt and driver monitoring apparatus which concern on 1st Embodiment. FIG. 4 is a diagram showing an example of a tomographic image generated by a state determination unit according to the first embodiment; It is a figure which shows the structure of the curvature sensor by 1st Embodiment. FIG. 4 is a diagram showing an arrangement example of strain gauges according to the first embodiment; 4 is a diagram showing a comparison of thicknesses of signal lines connected to the strain gauge and signal lines in the strain gauge according to the first embodiment; FIG. FIG. 4 is a diagram showing a connection example in which bridges and signal conversion modules are connected in a multi-to-one manner according to the first embodiment; It is a figure which shows the example of the shape of one part of the seatbelt by 1st Embodiment. FIG. 4 is a first diagram showing partial shape estimation processing of a shape estimation unit according to the first embodiment; It is a second diagram showing partial shape estimation processing of the shape estimation unit according to the first embodiment. It is a second diagram showing the internal configuration of the seat belt according to the first embodiment. FIG. 4 is a diagram showing an outline of processing for identifying a contact range X according to the first embodiment; FIG. 4 is a first diagram showing a processing flow of the driver monitoring device according to the first embodiment; FIG. It is a second diagram showing the processing flow of the driver monitoring device according to the first embodiment. FIG. 9 is a third diagram showing the processing flow of the driver monitoring device according to the first embodiment; FIG. 11 is a fourth diagram showing the processing flow of the driver monitoring device according to the first embodiment; FIG. 2 is a second diagram showing the functional configuration of the driver monitoring device according to the first embodiment; Fig. 10 shows a monitoring device and restraint belt according to a second embodiment;

<First Embodiment>
Hereinafter, a driver monitoring device, a driver monitoring method, and a program according to a first embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram showing a driver monitoring device and a seat belt according to the first embodiment.
As shown in FIG. 1, the driver monitoring device 2 is connected via a communication cable 3 to an electrical circuit formed on a flexible substrate incorporated in the seatbelt 1 .
As an example, the seat belt 1 has an electric circuit that includes at least a plurality of periodically arranged electrodes and a plurality of curvature sensors that are periodically arranged in parallel with the plurality of electrodes.
Also, the driver monitoring device 2 estimates the shape of the seat belt 1 based on the curvature data acquired via the curvature sensor built into the seat belt 1 . A driver monitoring device 2 determines the driver's condition based on the shape of the seat belt 1 .
The state of the driver may be the driver's consciousness, tomographic image, heart rate, ventilation state, body movement, and the like. The driver monitoring device 2 uses one or more of these driver states to determine whether the driver's state is normal or abnormal.

A flexible substrate 14 is provided inside the seat belt 1 . Specifically, the flexible substrate 14 is sandwiched between the two superimposed belts on the front and back sides forming the seat belt 1 .
FIG. 2 is a first diagram showing the internal configuration of the seat belt according to the first embodiment.
As shown in FIG. 2, the seatbelt 1 has a configuration in which a plurality of electrode pads 12A to 12H are arranged (periodically arranged) on a strip-shaped flexible substrate 14 at regular intervals P. As shown in FIG. Similarly, on the flexible substrate 14, a plurality of curvature sensors 150A to 150H are periodically arranged in parallel with the electrode pads 12A to 12H at equal intervals of a distance P. FIG. A plurality of electrode pads 12A to 12H are collectively referred to as electrode pads 12. As shown in FIG. A plurality of curvature sensors 150A to 150H are collectively referred to as a curvature sensor 150. FIG. Although eight electrode pads 12 and eight curvature sensors 150 are shown in FIG. 2, more electrode pads 12 and curvature sensors 150 may be provided.

Each of the electrode pads 12A to 12H and the curvature sensor 150 are provided inside the seatbelt 1 so as to be positioned in the measurement target range such as the chest and abdomen when the seatbelt 1 is wrapped around the driver's body. there is
The seat belt 1 may have strain gauges for each of the curvature sensors 150A-150H. The curvature sensor 150 has two strain gauges, and by using a two-active-gauge method in which a pair of strain gauges for each measurement point is connected to one bridge circuit, automatic temperature correction and high sensitivity of the curvature sensors 150A to 150H are achieved. , high precision can be achieved.
Alternatively, the seat belt 1 may have a temperature sensor at the same position on the back surface of each of the curvature sensors 150A to 150H. Then, the driver monitoring device 2 may perform temperature correction of the curvature data acquired by the curvature sensors 150A to 150H based on the temperature data acquired by the temperature sensors. By doing so, it is possible to realize high sensitivity and high accuracy of the curvature sensors 150A to 150H.

The measurement circuit 11 is an electric circuit that mediates exchange of electric signals between the driver monitoring device 2, the electrode pads 12A to 12H and the curvature sensors 150A to 150H. For example, the measurement circuit 11 includes a circuit for amplifying and A/D (Analog/Digital) converting the electrical signals output from the curvature sensors 150A to 150H.

FIG. 3 is a first diagram showing the functional configuration of the driver monitoring device according to the first embodiment.
The driver monitoring device 2 according to the first embodiment is composed of a computer. The driver monitoring device 2 may be incorporated within the car navigation system.

As shown in FIG. 3, the driver monitoring device 2 includes a CPU (Central Processing Unit) 200 that controls the overall operation, and a work area of the CPU 200 when executing a measurement program used for EIT measurement. and a HDD (Hard Disk Drive) 211 as storage means for storing various programs and tomographic images and the like acquired by the state determination unit 201 .
Further, the operation input unit 212 includes, for example, operation buttons, a touch panel, etc., and receives input of various operations by an operator such as a driver. The image display unit 213 is a liquid crystal display or the like, and displays information necessary for EIT measurement, an acquired tomographic image, and the like.
The external interface 214 is a communication interface for communicating with an external device. Particularly in this embodiment, the external interface 214 is connected to the seatbelt 1 via a dedicated communication cable 3 and acquires various signals from the seatbelt 1. It is a functional part that
CPU 200 , RAM 210 , HDD 211 , operation input section 212 , image display section 213 and external interface 214 are electrically connected to each other via system bus 215 .

As shown in FIG. 3, the CPU 200 executes a predetermined measurement program while the seat belt 1 is in use, and functions as a state determination section 201 and a shape estimation section 202 during execution.
The state determination unit 201 acquires a tomographic image of the measurement target portion X while energizing the plurality of electrode pads 12A to 12H and acquiring voltage signals generated between the electrode pads 12A to 12H.
Further, the shape estimator 202 estimates the shape of the seat belt 1 based on the curvature data acquired via the curvature sensors 150A-150H.

FIG. 4 is a diagram for explaining the configuration of the seat belt and the driver monitoring device according to this embodiment.
The function of the state determination unit 201 will be described below with reference to FIGS. 4 and 5. FIG. As shown in FIG. 4, a current source I and a voltmeter V are connected between the electrode pads 12A-12H. The state determination unit 201 has a function of controlling the current source I and the voltmeter V. FIG.

The state determination unit 201 controls a predetermined weak current to flow between a pair of electrode pads among the electrode pads 12A to 12H (for example, between the electrode pads 12A and 12B) via the current source I. . The state determination unit 201 measures the potential difference generated between each of the other electrode pads (electrode pads 12C to 12H) through the voltmeter V while a weak current is passed through the pair of electrode pads. The resistivity distribution in the tomography of the measurement target portion X can be obtained by repeatedly changing the electrode pads through which the current flows to 12B and 12C, 12C and 12D, . . . and repeatedly measuring the potential difference.

The state determination unit 201 generates a tomographic image using, for example, a general back projection method, based on the resistivity distribution on the tomographic plane to be measured obtained as described above. The state determination unit 201 causes the image display unit 213 to display the generated tomographic image, thereby allowing the driver, the ambulance crew, and the like to visually recognize the tomographic image. A well-known technique may be used as a technique for generating a tomographic image using EIT in the state determination unit 201 .
Although FIG. 4 shows a situation in which the current source I and the voltmeter V are provided between different electrode pads 12 , the current source I and the voltmeter V may be provided between each electrode pad 12 . A four-electrode method or a two-electrode method may be used to measure the current value and voltage value between the electrode pads 12 . Moreover, any structure of the electrode pad 12 may be applied to the electrode pad 12 .

FIG. 5 is a diagram showing an example of a tomographic image generated by the state determination unit.
FIG. 5 is a tomographic image of the chest of the measurement subject acquired by the state determination unit 201, and the regions with higher electrical impedance are shown in darker shades. According to FIG. 5, it can be seen that there are left and right lung fields whose electrical impedance is measured to be high due to the presence of air.
As a method for the state determination unit 201 to generate a tomographic image, a method using the finite element method (FEM) in addition to the above-described backprojection method, or a method combining the finite element method and the backprojection method can be considered. be done. When the back projection method is used, the state determination unit 201 can image only relative changes with a certain state as a reference. A tomographic image based on the modulus [Ωm] can be formed.

FIG. 6 is a diagram showing the configuration of a curvature sensor.
The curvature sensor 150 measures the curvature of the seat belt 1 at the position where the curvature sensor 150 is arranged. As shown in FIG. 6, the curvature sensor 150 includes a bridge (Wheatstone bridge) 151 combining resistors 152-1 and 152-2 and strain gauges 153-1 and 153-2, and an amplifier 156. be done. Bridge 151 receives a DC voltage from power supply 111 during curvature measurement. Current from the power supply unit 111 flows through the bridge 151 to ground (zero potential point).

The output of curvature sensor 150 is transmitted to driver monitoring device 2 via A/D converter (analog-digital converter) 157 and serial communication circuit 114 .
Resistors 152-1 and 152-2 are collectively referred to as resistor 152 below. Also, the strain gauges 153-1 and 153-2 are collectively referred to as the strain gauge 153. FIG.
The function of each circuit shown in FIG. 6 may be printed on the flexible substrate 14 .

FIG. 7 is a diagram showing an arrangement example of strain gauges.
The figure shows an example of a cross section of the seat belt 1 viewed from the side, and an arrow B11 indicates the longitudinal direction of the seat belt 1. As shown in FIG.
All of the strain gauges 153 are arranged so that the direction in which strain is detected coincides with the longitudinal direction of the seat belt 1 . Further, as shown in FIG. 7, the strain gauges 153-1 and 152-2 are arranged with the flexible substrate 14 interposed therebetween. For example, the strain gauge 153-1 is arranged on the front band 41 side of the seat belt 1 when viewed from the flexible substrate 14, and the strain gauge 153-2 is arranged on the back band 42 side of the seat belt 1 when viewed from the flexible substrate 14. there is

Due to this arrangement, when the flexible substrate 14 is bent, a difference occurs between the impedance of the strain gauge 153-1 and the impedance of the strain gauge 153-2. When the driver wears the seatbelt 1 and the flexible substrate 14 bends convexly on the front side of the seatbelt 1 and concavely on the back side, the strain gauge 153-1 arranged on the front side of the seatbelt 1 stretches. the impedance increases. On the other hand, the strain gauge 153-2 arranged on the back side of the seat belt 1 shrinks and its impedance becomes small.

Due to this impedance difference, a voltage (potential difference) is generated between points P11 and P12 in FIG. The magnitude of the voltage between the points P11 and P12 indicates the bending magnitude of the seat belt 1 at the position of the strain gauge 153 on the seat belt 1 (the position of the curvature sensor 150).
Amplifier 156 converts the voltage between point P11 and point P12 into the curvature of seat belt 1 at the installation position of strain gauge 153 . Specifically, a calibration curve showing the relationship between the voltage between the points P11 and P12 and the curvature of the seat belt 1 is obtained in advance, and the amplifier 156 converts the voltage between the points P11 and P12 to It is set to amplify according to this calibration curve.

Alternatively, the bridge 151 may have only one strain gauge 153 . Specifically, the bridge 151 may have a resistor in place of either one of the strain gauges 153-1 and 153-2. As the resistance in this case, a resistance that exhibits the same resistance as when the strain gauge 153 is not bent is used.
On the other hand, when the bridge 151 has one strain gauge 153 as shown in FIG. The accuracy of sensor 150 is improved. In addition, since the bridge 151 includes one strain gauge 153, it is less susceptible to temperature changes than when the bridge 151 includes only one strain gauge 153. FIG.

The wiring inside the strain gauge 153 is thinned, and the wiring connected to the strain gauge 153 is thickened. Thereby, the accuracy of the curvature sensor 150 can be improved. This point will be described with reference to FIG.
FIG. 8 is a diagram showing a comparison of the thickness of the signal line connected to the strain gauge and the signal line inside the strain gauge.
In the figure, a wire W11 inside the strain gauge 153 and a wire W12 connected to the strain gauge 153 are shown.

When the strain gauge 153 is bent, the impedance of the strain gauge 153 changes due to the change in the length or width of the wiring W11 or both. The strain gauge 153 indicates the magnitude of bending with this change in impedance.
The width of the wiring W11 is narrowed (the wiring W11 is thinned) so that the impedance of the strain gauge 153 can easily change. As a result, when the strain gauge 153 is bent and the width of the wiring W11 changes, the rate of change from the original width increases.

On the other hand, in order to accurately measure the impedance of the strain gauge 153, it is preferable that the resistance between the strain gauge 153 and the impedance detection circuit (amplifier 156 in the example of FIG. 6) be small. Therefore, the width of the wiring W12 is increased (thickening the wiring W12).
By thinning the wiring in the strain gauge 153 and thickening the wiring connected to the strain gauge 153 in this manner, the accuracy of the curvature sensor 150 can be improved.

The A/D converter 157 converts an analog signal (for example, a voltage value proportional to curvature) output by the amplifier 156 into a digital signal.
The serial communication circuit 114 transmits the digital signal output from the A/D converter 157 to the driver monitoring device 2 through serial communication. Thereby, the serial communication circuit 114 transmits the digital signal output by the A/D converter 157 to the driver monitoring device 2 . The serial communication circuit 114 is provided, for example, for each curvature sensor 150 , and the first serial communication section 110 includes these serial communication circuits 114 .

Various serial communication methods such as SPI (Serial Peripheral Interface) or I2C (Inter-Integrated Circuit) (I2C is a registered trademark) can be used as the communication method of the serial communication circuit 114 .
By performing serial communication by the serial communication circuit 114, it is possible to communicate the sensor value of the curvature sensor 150 with a small number of wires of about 3 to 5 wires. Since a large number of wires are not required, it is possible to avoid an increase in the size of the seat belt 1, such as a wide or thick band forming the seat belt.

A combination of the amplifier 156 , the A/D converter 157 and the serial communication circuit 114 is hereinafter referred to as a signal conversion module 181 . The signal conversion module 181 converts the analog signal (the voltage between the points P11 and P12) from the bridge 151 into a digital signal representing the curvature, and further into a digital signal conforming to the serial communication standard.
Here, the signal conversion module 181 is integrated into one structure, such as forming the signal conversion module 181 on one IC chip, or forming the signal conversion module 181 on one substrate. This eliminates the need to design the signal conversion module 181 for each curvature sensor 150 (bridge 151 of the curvature sensor 150). In this respect, when designing the seat belt 1, the signal conversion module 181 can be arranged relatively easily.

Note that one signal conversion module 181 may transmit the curvatures from a plurality of bridges 151 .
FIG. 9 is a diagram showing a connection example in which bridges and signal conversion modules are connected in a multi-to-one manner.
In the example shown in the figure, four bridges 151 are connected to the signal conversion module via multiplexers 182 .

The multiplexer 182 switches the bridge 151 connected to the signal conversion module 181 in a time division manner. The signal conversion module 181 converts the voltage of the bridge 151 (the voltage between points P11 and P12 in FIG. 6) connected via the multiplexer 182 into a digital signal indicating curvature and transmits the digital signal by serial communication. do. This allows the curvature to be transmitted with a relatively small number of signal conversion modules.

On the other hand, when the bridge 151 and the signal conversion module are arranged one-to-one, the signal conversion module 181 is arranged near the bridge 151 . This can prevent the S/N ratio (Signal To Noise Ratio) of the signal (voltage in the bridge 151) acquired by the signal conversion module 181 from decreasing. In this respect, the curvature sensor 150 can measure curvature with high accuracy.

Further, when the bridge 151 and the signal conversion module 181 are arranged one-to-one, the wiring length between the bridge 151 and the signal conversion module 181 is the same regardless of the combination of the bridge 151 and the signal conversion module 181. align. This can reduce variation in curvature measurement accuracy for each combination of the bridge 151 and the signal conversion module 181 . The signal conversion module 181 may be built into the measurement circuit 11 .

The shape estimator 202 detects the contact (approaching) range X of the measurement object (chest or abdomen) on the seat belt 1 using the measurement results of the curvature sensor 150 or the like, and estimates the shape of the seat belt.
The shape estimation unit 202 communicates with the measurement circuit 11 by serial communication. In particular, the shape estimator 202 receives various data transmitted from the measurement circuit 11, such as curvature measurements.
The shape estimator 202 determines whether to start detecting the contact area X and estimating the shape of the seat belt. Specifically, the shape estimating section 202 determines whether or not the conditions for starting the processing of detecting the contact range X of the seat belt with respect to the measurement object and estimating the shape of the seat belt are satisfied. The driver monitoring device 2 determines that the start condition is satisfied when, for example, a switch provided on the buckle that engages the seat belt 1 is turned on, and the state determination unit 201 and the shape estimation unit 202 determine that the start condition is satisfied. to notify. The switch provided on the buckle may be structured to be turned on when the metal plate provided on the seat belt and the buckle are engaged when the seat belt is used. By determining that the start condition is satisfied, the state determination unit 201 and the shape estimation unit 202 start processing.

When determining that the start condition is satisfied, the shape estimating unit 202 estimates the seat belt shape of the contact range X of the seat belt with respect to the measurement target based on the sensor value of the curvature sensor 150 (curvature detected by the curvature sensor 150).
The shape estimation processing performed by the shape estimation unit 202 will be described with reference to FIGS. 10 to 12. FIG.

FIG. 10 is a diagram showing an example of the shape of a portion of the seat belt.
The figure shows a state in which the flexible substrate 14 and the plurality of curvature sensors 150 provided on the flexible substrate 14 are bent. The partial shape of the flexible substrate 14 can be regarded as the partial shape of the seat belt 1 (the partial shape of the belt portion). Here, the curvature sensors 150 are described as curvature sensor 150-1, curvature sensor 150-2, curvature sensor 150-3, .

In the example of FIG. 10, the curvature sensors 150 are arranged at regular intervals (distance d). A range of distance d is assumed centered on each of the curvature sensors 150, and the ends of these ranges are indicated by points P0, P1, P2, P3, . The partial shape estimator 241 approximates each of these ranges with an arc of curvature indicated by the curvature sensor 150 to obtain the partial shape.
It is also assumed that the curvature of curvature sensor 150-1 is C1, the curvature of curvature sensor 150-2 is C2, and the curvature of curvature sensor 150-3 is C3.

FIG. 11 is a first diagram showing partial shape estimation processing of the shape estimation unit.
FIG. 11 shows, in a coordinate system with the origin O as a reference, a curvature sensor 150-1, one end (point P0) and the other end (point _P1 ) of the range of distance d centered on the curvature sensor 150-1. is shown. The value of the distance d is a known value, and the shape estimator 202 acquires the curvature _C1 measured by the curvature sensor 150a. The shape estimator 202 calculates the curvature radius _R1 from the curvature _C1 based on Equation (1).

Formula (1) is a general formula, in which C indicates curvature and R indicates the radius of curvature.
Based on the radius of curvature R ₁ and the curvature C ₁ , the shape estimating unit 202 calculates the central angle of an arc that approximates the range of the distance d centered on the curvature sensor 150-1 (the central angle ) θ ₁ is calculated by equation (2).

Formula (2) is a general formula, in which θ indicates the central angle and C indicates the curvature. Also, the distance d indicates the length of the arc. The center point of the sector is called _O1 . Shape estimating section 202 uses the coordinates of central point O ₁ of the fan shape, the coordinates of point P ₀ , and the central angle θ ₁ to determine the range of distance d centered on curvature sensor 150-1 by Equation (3). , and the coordinates of the point _P1 on the other end that is different from the point _P0 of .

Here, P ₀ , P ₁ , and O ₁ are column vectors indicating the coordinates of point P ₀ , point P ₁ , and center point O _{1 ,} respectively.
The coordinates of the central point _O1 of the fan shape can be calculated from the origin O of the coordinate system, the point _P0 , and the value of the radius of curvature _R1 . In addition, the center point of an arc (the center point ) O _i+1 can be calculated by equation (4).

In Equation (4), O _i+1 , P _i , O _i are column vectors indicating coordinates of center point O _i+1 , point P _i , center point O _{i ,} respectively. R _i and R _i+1 are the curvature radii obtained from the curvatures C _i and C _i+1 by Equation (1), respectively.
Assuming that the point at one end of the arc approximating the range of distance d centered on the curvature sensor 150-i is P _i−1 , the point P _i at the other end of the arc can be calculated by equation (5). .

In equation (5), P _i-1 is a column vector indicating the coordinates of point P _i-1 . Also, θ _i indicates the central angle of an arc (central angle of a sector having this arc) that approximates the range of distance d centered on curvature sensor 150-i.

FIG. 12 is a second diagram showing partial shape estimation processing of the shape estimation unit.
FIG. 12 shows an example in which the processing shown in FIG. 11 is repeated. As described above, the shape estimating unit 202 calculates the coordinates of the point P i from the coordinates of the point P _i−1 based on the curvature C _i and the distance d (arc length) measured by the curvature sensor 150- _i . can do. Note that the point _P0 in the first process of partial shape estimation may be coordinates arbitrarily set in the coordinate system.
The shape estimation unit 202 sequentially calculates the coordinates of the points P ₁ , P ₂ , P ₃ , . As a result, the shape estimator 202 estimates the shape of the portion of the seat belt 1 where the curvature sensor 150 is arranged (including the portion between the curvature sensors 150 and 150) by approximating it with continuous circular arcs. can be done.

The shape estimator 202 estimates the shape of the portion where the curvature sensors 150 are arranged as described above by approximating them with continuous arcs based on information such as curvature obtained from the plurality of curvature sensors 150 provided on the seat belt 1, Thereby, the three-dimensional shape of the contact range X of the seat belt with respect to the whole seat belt 1 or the object to be measured is calculated. The driver monitoring device 2 stores in advance in a storage unit such as the HDD 211 3D modeling data of a plurality of three-dimensional shapes of seat belts on the chest and abdomen according to different body types. In this case, the shape estimating unit 202 compares the calculated overall three-dimensional shape of the seat belt 1 with 3D modeling data of a plurality of three-dimensional shapes and a plurality of three-dimensional shapes of the seat belt according to the human body type. The shape estimator 202 identifies 3D modeling data similar to the current three-dimensional shape of the driver. The shape estimation unit 202 identifies the contact range X of the seat belt 1 recorded in the storage unit in association with the identified 3D modeling data. The information on the range X of the seat belt 1 differs depending on the body type of the person, and indicates the contact range X of the seat belt with respect to the measurement target when the seat belt 1 is worn according to the body type of the person. Since the range of the seat belt 1 that contacts the chest and abdomen of the body differs depending on the body type, the driver monitoring device 2 stores information on the contact range X of the seat belt when worn according to the body type of the person. The driver monitoring device 2 may store information on the set position of the seat (seat) 4 and the contact range X of the seat belt when the seat belt is worn according to the combination of the body shape of the person. Then, the shape estimating unit 202 detects the current setting position of the seat 4 from a position detection device provided on the seat 4 or the like, and detects the seat belt recorded in the storage unit in association with the information on the setting position of the seat. 3D modeling data of a plurality of three-dimensional shapes may be acquired, and the data may be compared with the current calculated three-dimensional shape of the seat belt 1 .

The shape estimating section 202 outputs information on the specified contact range X of the seat belt 1 to the state determining section 201 . Based on the information on the contact range X, the state determination unit 201 identifies the electrode pads 12 included in that range. The state determination unit 201 determines the specified electrode pad 12 as the electrode pad 12 to be operated. The state determination unit 201 generates a tomographic image of the measurement target portion X while energizing the specified plurality of electrode pads 12 and acquiring voltage signals generated between two of the electrode pads 12 . good too. Since the driver monitoring device 2 identifies the electrode pads 12 based on the body shape of the person and the setting position of the seat 4, it is not necessary to energize all the electrode pads 12 provided on the seat belt. The driver monitoring device 2 has a number of setting positions such as the angle of the back of the seat 4 and the front and rear positions of the seating surface of the seat 4. 3D modeling data of the shape may be stored.

The state determination unit 201 may specify the curvature sensor 150 included in the contact range X based on the information of the contact range X acquired from the shape estimation unit 202, and determine the curvature sensor 150 to operate only the curvature sensor 150. good. According to this process, the state determination unit 201 estimates the range in which the seat belt 1 contacts the driver, and drives the electrode pads 12 or the curvature sensor 150 located in the contact range.

The state determination unit 201 may estimate the range in which the seat belt 1 contacts the driver based on the voltage signal generated between the electrode pads 12 . For example, the driver monitoring device 2 causes high-frequency current to flow between two adjacent electrode pads 12 . An electric field E is then generated between the electrode pads 12 . When, for example, a body enters this electric field region, the electric field changes and the voltage value measured by the voltmeter V changes. The driver monitoring device 2 uses a voltmeter V connected in parallel with the current source I to constantly monitor changes in impedance due to the influence of objects such as the body on the electric field region from fluctuations in the voltage value. Note that the impedance value is obtained by dividing the voltage value by the current value. The driver monitoring device 2 can determine that the area of the seat belt 1 in the vicinity of the electrode pad 12 is in contact with the body when the impedance change is lower than a predetermined value.
The electrode pads 12 shown in FIG. 2 may be electrode pads 12 used only for generating a tomographic image by EIT. In this case, a plurality of dedicated electrode pads for detecting the contact range X may be periodically arranged at even shorter intervals on the substrate of the seatbelt 1 .

FIG. 13 is a second view showing the internal construction of the seatbelt.
In FIG. 13, the electrode pads 12A to 12H and the strain gauges 13A to 13H are omitted in order to avoid complication of the drawing. Above they are arranged in a periodic arrangement.
As shown in FIG. 13, the seat belt 1 according to the present embodiment is periodically arranged along its longitudinal direction (in parallel with the electrode pads 12A to 12H, etc.) at an interval α shorter than the interval P. Contact area measuring electrode pads 301, 302, . . . , 30f may be provided.

The state determination unit 201 may specify the heart area and the lung area within the contact area X. FIG. For example, based on the information of the contact range X obtained from the shape estimating section 202, the state determination section 201 determines the heart range and the lung range of the contact range X as the heart range and the lung range with respect to the contact range X stored in advance. may be specified based on information on the position of the .

14A and 14B are diagrams showing an outline of the process of specifying the contact range X. FIG.
FIG. 14(a) shows how the seat belt 1 is in contact with the object to be measured.
As shown in FIG. 14(a), the case where the seat belt 1 is in contact with the person to be measured from position A1 to position A2 will be described. The seat belt 1 is close to the human body M in the contact range X from the position A1 to the position A2, and is separated from the human body M in other regions.
FIG. 14(b) shows in detail the vicinity of the position A1 of the seat belt 1 in the state shown in FIG. 14(a). For example, it is assumed that electrode pads 301, 302, 303, 304, 305, and 306 are arranged near position A1 as shown in FIG. 14(b). In this case, the shape estimation unit 202 sequentially changes the electrode pad pairs such as between the electrode pads 301 and 302, between the electrode pads 303 and 302, between the electrode pads 303 and 304, and Acquire the electrical impedance between pairs. The electrical impedance acquired by the shape estimation unit 202 is a value dependent on the electric fields E0, E1, .

Here, attention is paid to the paths of the electric fields E0 to E4 generated between the electrode pad pairs. As shown in FIG. 14(b), the electrode pads 301a and 302 are not close to the human body M, and the electric field E0 generated therebetween is generated in the atmosphere. On the other hand, since the electrode pads 305 and 306 are close to the human body at the position A1, the electric field E4 generated therebetween passes through the human body M (in vivo). Therefore, the electrical impedance between electrode pads 305 and 306 is measured to be lower than the electrical impedance between electrode pads 301 and 302 .
That is, since the electrode pads 301, 302, . As the area increases, the electrical impedance corresponding to each electric field E0-E4 gradually decreases.

In this way, in the region where the seat belt 1 comes close to the human body M, the electrical impedance between the electrode pad pairs belonging to that region is measured to be low, and in the region where the seat belt 1 does not come close (contact) with the human body M, A high electrical impedance is measured between the electrode pad pairs belonging to the region. Therefore, the shape estimating unit 202 compares the electrical impedance with a preset threshold value, and identifies the electrode pads constituting the electrode pads for which the electrical impedance lower than the threshold value is acquired as the electrode pads located in the contact range X.

After starting the process, the shape estimator 202 repeatedly detects seat belt shape information at predetermined time intervals. The shape estimating unit 202 detects the body movement such as the distance and period of body movement based on the shape of the contact area X of the seat belt when the seat belt is worn. The shape estimation unit 202 outputs the body movement distance and cycle to the state determination unit 201 .

The state determination unit 201 may generate a tomographic image, estimate the shape of the seat belt 1, and estimate the heart rate and ventilation volume.
The state determination unit 201 generates a tomographic image of the human body corresponding to the position of the contact range X at short time intervals. The state determination unit 201 detects movement of the shape of the lungs and chest in the tomographic image by image processing, specifies the cycle of contraction and expansion of the size, and calculates the heart rate per unit time based on the cycle. may In addition, the state determination unit 201 detects movement of the shape of the lungs and chest by image processing, identifies changes in the shape of the lungs and chest during contraction and expansion, and determines the ventilation volume per unit time based on the change. may be calculated.

The driver monitoring device 2 may calculate the heart rate and ventilation volume based on the high-frequency current applied to the electrode pads 12 . The state determination unit 201 applies a high frequency current to the electrode pad 12 . Based on the input signal from the voltmeter V, the state determination unit 201 can thereby detect the impedance change caused by the air in and out of the lungs associated with respiration. More specifically, since the impedance of air is high, when the amount of air flowing into the lungs decreases (corresponding to the amount of exhaled ventilation), the impedance value of the lungs decreases accordingly. Therefore, when the lung expands, the amount of air increases (corresponding to the amount of ventilation to be inhaled), so the state determination unit 201 detects that the impedance value has increased. On the other hand, when the lungs contract and air flows out of the lungs, the state determination unit 201 detects that the impedance has changed in the lower direction. A measurement of lung ventilation can thus be performed by the driver monitoring device 2 .

In addition, the amount of blood in the heart changes depending on the pulsation of the heart. The state determination unit 201 applies a high frequency current to the electrode pad 12 . Accordingly, based on the input signal from the voltmeter V, the state determination section 201 can detect the impedance change caused by the increase or decrease in the blood volume in the heart accompanying the heartbeat. More specifically, since the impedance of blood is low, the impedance of the heart increases as the blood volume of the heart decreases. Therefore, when the heart contracts, the state determination unit 201 detects that the impedance has changed to a higher direction. On the other hand, when the heart expands and blood flows into the heart, the state determination unit 201 detects that the impedance has changed in the lower direction. In this way, the driver monitoring device 2 can measure heart rate information.

In addition, since the driver monitoring device 2 directly detects an increase or decrease in blood volume in the heart from impedance changes, heartbeat information can be detected with higher accuracy than conventional devices. The state determination unit 201 detects the heart rate per unit time, for example, based on the number of peak values per unit time based on impedance changes.

The voltmeter V measures the voltage and outputs it to the state determination unit 201 in the measurement of the ventilation volume described above. The state determination unit 201 calculates the impedance value based on the voltage measurement result of the voltmeter V. FIG. Then, the state determination unit 201 determines a change from the impedance value in the stable state. The state determination unit 201 converts the amount of change in impedance into a ventilation volume based on the amount of change in impedance, a correction formula, a correction table, or the like. The state determination unit 201 repeatedly calculates the ventilation volume at short time intervals (for example, at intervals of several milliseconds). Then, the state determination unit 201 records the ventilation volume at each time in the memory according to the passage of time.

In the heartbeat measurement described above, the voltmeter V measures the voltage and outputs it to the state determination unit 201 . Then, the state determination unit 201 calculates the impedance value based on the voltage measurement result of the voltmeter V. FIG. The state determination unit 201 repeatedly calculates the impedance value at short time intervals (for example, at intervals of several milliseconds). The state determination unit 201 records the amount of change in impedance at each time in memory according to the passage of time. The state determination unit 201 calculates the heart rate per unit time based on the number of peak values per unit time based on the impedance change, and records it in memory. By the above processing, the heartbeat information at each time is accumulated in the memory according to the passage of time.
The state determination unit 201 performs control so as to switch between the acquisition of the ventilation volume and the acquisition of the heart rate. Alternatively, if the heart range and the lung range for the contact range X can be specified, the state determination unit 201 acquires the ventilation volume from the signal of the electrode pads 12 located in the lung range, You may make it acquire a heart rate from the signal of.

The state determination unit 201 determines whether the driver's state is normal or abnormal using one or more of the shape of the seat belt 1, the tomographic image, the heart rate, and the ventilation volume. The shape of the seat belt 1 used by the state determination unit 201 for the state of the driver may be the shape of the contact range X. FIG. Alternatively, the state determination unit 201, when used for the driver's state, uses only the curvature data from the curvature sensor 150 provided in the seat belt 1 to determine the driver's body movement, heart rate, and ventilation volume. Either one or more may be used to determine whether the driver's condition is normal or abnormal. The movement of the body is, for example, the movement of the driver's body facing the steering wheel, which repeats the movement of approaching the steering wheel and moving away from the steering wheel. The state determination unit 201 determines the movement of the body using the conversion of the curvature data values of the curvature sensor 150 at predetermined intervals. By estimating body movement, heart rate, and ventilation volume only from changes in the shape of the seat belt 1, the state determination unit 201 gives an electric signal to the chest even for a driver who has a heart rate pacemaker in his/her body. The driver's condition can be determined without

The state determination unit 201 may determine whether the driver feels drowsy based on the body movement distance, cycle, and body movement pattern determined based on the shape of the seat belt.
Also, the state determination unit 201 may detect the breathing interval and the ventilation volume based on the change in the lung region obtained by the image processing of the tomographic image. The state determination unit 201 determines whether the breathing interval and the ventilation volume have increased or decreased from the breathing intervals and the ventilation volume detected in the initial period of driving, or the driver's drowsiness and ventilation based on the pattern of repeated increases and decreases. Other physical conditions may be determined.
The state determination unit 201 also detects the heart rate per unit time obtained by image processing of the tomographic image. The state determination unit 201 detects drowsiness or other physical conditions of the driver based on whether the heart rate has increased or decreased from the heart rate detected during the initial period of driving, or based on the pattern of repeated increases and decreases. status may be determined.
Further, the condition determination unit 201 may determine the drowsiness or other physical condition of the driver by combining the breathing interval and the pattern of increase or decrease in the heart rate.
Note that the state determination unit 201 may use a known technique to determine the state of the driver using the heart rate, ventilation volume, body movement, and breathing interval.

FIG. 15 is a first diagram showing the processing flow of the driver monitoring device.
The shape estimation unit 202 of the driver monitoring device 2 acquires curvature data from the curvature sensor 150 (step S101). The shape estimator 202 determines the shape of the seat belt from the curvature data (step S102). The shape estimation unit 202 outputs information indicating the shape of the seat belt to the state determination unit 201 . The information indicating the shape of the seat belt 1 may be 3D modeling data of the shape, or may be the curvature values themselves obtained from the curvature sensors 150 . The state determination unit 201 calculates state information such as body motion, breathing interval, ventilation volume, etc. from the information indicating the shape of the seat belt 1 (step S103). The state determination unit 201 determines whether the driver is in a bad state using one or more of the state information (step S104). If the condition determining unit 201 determines that the driver is in a bad condition, it outputs warning information (step S105). The warning information is a signal for sounding an alarm, which is a warning sensor. The state determination unit 201 may issue a warning by vibrating a vibrating device, which is a warning sensor provided in the seat and steering wheel.
When the driver monitoring device 2 performs the processing shown in FIG. 15, the seat belt 1 may be provided with a plurality of curvature sensors 150 even if the electrode pad 12 is not provided.

FIG. 16 is a second diagram showing the processing flow of the driver monitoring device.
The shape estimator 202 of the driver monitoring device 2 acquires electrical signals from the electrode pads 12 (step S201). The state determination unit 201 generates a tomographic image using the EIT technique described above (step S202). The state determination unit 201 uses the tomographic image to calculate state information such as breathing interval, ventilation volume, and heart rate based on changes in the image over time (step S203). The state determination unit 201 determines whether the driver's state is bad using one or more of the state information (step S204). If the condition determining unit 201 determines that the driver is in a bad condition, it outputs warning information (step S205). The warning information may be an audible alarm. The state determination unit 201 may issue a warning by vibrating vibrating devices provided in the seat and the steering wheel. Also, the warning information may be a control signal for a control device such as an automatic brake. By outputting the warning information to the device that controls the vehicle in this manner, more active danger avoidance control may be performed in combination with automatic steering (automatic driving) technology.
When the driver monitoring device 2 performs the processing shown in FIG. 16, the seat belt 1 may be provided with a plurality of electrode pads 12 even if the curvature sensor 150 is not provided.

FIG. 17 is a third diagram showing the processing flow of the driver monitoring device.
The shape estimation unit 202 of the driver monitoring device 2 acquires curvature data from the curvature sensor 150 (step S301). The shape estimator 202 determines the shape of the seat belt 1 from the curvature data (step S302). Shape estimation section 202 outputs information indicating the shape of seat belt 1 to state determination section 201 . The information indicating the shape of the seat belt 1 may be 3D modeling data of the shape, or may be the curvature values themselves obtained from the curvature sensors 150 . The state determination unit 201 calculates state information according to the shape of the seat belt 1, such as body motion, breathing interval, ventilation volume, etc., from the information indicating the shape of the seat belt 1 (step S303).

The shape estimator 202 of the driver monitoring device 2 acquires electrical signals from the electrode pads 12 (step S304). The state determination unit 201 generates a tomographic image using the EIT technique described above (step S305). Using the tomographic image, the state determination unit 201 calculates state information such as breathing interval, ventilation volume, and heart rate based on changes in the image over time (step S306). The condition determination unit 201 determines whether the condition of the driver is bad using one or more of the condition information calculated in step S303 and the condition information calculated in step S306 (step S307). Subsequent processing is the same as the processing shown in FIGS. If the condition determining unit 201 determines that the driver is in a bad condition, it outputs warning information (step S308).

FIG. 18 is a fourth diagram showing the processing flow of the driver monitoring device.
The shape estimation unit 202 of the driver monitoring device 2 acquires curvature data from the curvature sensor 150 (step S401). The shape estimator 202 determines the shape of the seat belt 1 from the curvature data (step S402). The shape estimation unit 202 outputs information indicating the shape of the seat belt to the state determination unit 201 . The information indicating the shape of the seat belt 1 may be 3D modeling data of the shape, or may be the curvature values themselves obtained from the curvature sensors 150 . The shape estimator 202 identifies the contact range X based on the shape of the seat belt (step S403), and outputs information on the range to the state determination unit 201. FIG. Based on the contact range X, the state determination unit 201 determines to operate the electrode pads 12 and the curvature sensor 150 located in the range, and determines to energize (step S404). Thereafter, the state determining unit 201 and the shape estimating unit 202 receive signals from the electrode pads 12 and the curvature sensor 150 determined to be energized.

The shape estimation unit 202 determines the shape of the seat belt based on the curvature data acquired from the curvature sensor 150 in operation (step S405). , state information such as ventilation volume is calculated (step S406). The shape estimation unit 202 acquires electrical signals from the electrode pads 12 (step S407). The state determination unit 201 generates a tomographic image using the EIT technique described above (step S408). The state determination unit 201 uses the tomographic image to calculate state information such as breathing interval, ventilation volume, and heartbeat based on changes in the image over time (step S409). The condition determination unit 201 determines whether the condition of the driver is bad using one or more of the condition information calculated in step S406 and the condition information calculated in step S409 (step S410). If the condition determining unit 201 determines that the driver is in a bad condition, it outputs warning information (step S411).
Although the processing flow shown in FIGS. 15 to 17 does not include the process of specifying the contact range X, the process of specifying the contact range X may be included. Furthermore, the processing flows shown in FIGS. 15 to 18 may include the processing described in paragraphs 0083 to 0087 above.
According to the processing of the driver monitoring device described above, it is possible to detect the state of the driver's body, issue a warning to the driver, or use it for control to assist the driving operation. The control that assists the driving operation may be, for example, brake control such as automatic deceleration.
Further, according to the driver monitoring device described above, it is possible to easily determine an abnormality in the health condition of the driver during driving without using a special device.

FIG. 19 is a second diagram showing the functional configuration of the driver monitoring device according to the first embodiment.
The driver monitoring device 2 may further have functions of a recording unit 203, a display processing unit 204, and a correction unit 205 by executing a program.
The recording unit 203 records one or more of the tomographic image, heart rate, ventilation state, and other driver's states in the HDD 211 . By the processing of the recording unit, it is possible to grasp the state of the driver's body and consciousness during past driving.
The display processing unit 204 displays on a monitor such as the image display unit 123 one or more of the tomographic image, heart rate, ventilation state, and other driver's conditions.
The correction unit 205 corrects the value output by the curvature sensor based on the shape of the seat belt 1 when the seat belt 1 is in a predetermined state in which it is not used. For example, a situation in which the seat belt 1 is not used is detected by some kind of detection function. When the seat belt 1 is not in use, for example, the output of the curvature sensor 150 at the seat belt 1 is a predetermined value. If the value of the curvature sensor 150 is not the predetermined value while the seat belt 1 is not in use, the difference between the predetermined value and the currently acquired value is used as the correction value.

The seat belt 1 described above may have a mechanism that allows it to be removed from the vehicle body. When an accident occurs, an emergency worker or the like removes the seat belt 1 from the vehicle body, wraps it around the passenger, and activates the seat belt 1 and the driver monitoring device 2. - 特許庁Then, the state of the occupants of the vehicle in which the accident occurred may be monitored by the processing of the first embodiment. In this case, the seat belt 1 and the driver monitoring device 2 may have a function of being able to communicate and connect via wireless communication. Moreover, the seat belt 1 has a function of wireless communication with a mobile terminal, and the mobile terminal may have a function of a driver monitoring device. In this case, each signal received from the seat belt 1 is processed, and the portable terminal performs the above-described processing equivalent to that of the driver monitoring device. As a result, it is possible to monitor the state of the passengers in the vehicle using the portable terminal.
Since the internal structure of the seat belt 1 is composed of the flexible substrate 14 on which the circuit pattern is printed, the condition of the person to be measured can be monitored by wrapping the seat belt around the human body as described above.
The seatbelt 1 and the driver monitoring device 2 described above may be mounted on various moving bodies such as cars and airplanes on which persons to be measured ride.

<Second embodiment>
FIG. 20 is a diagram showing a monitoring device and restraint belt according to the second embodiment.
In the above description, the driver monitoring device 2 that detects the state of the driver using the seat belt 1 has been described. However, the restraint belt 7 having the same function as the seat belt 1 described in the first embodiment and the monitoring device 6 having the same function as the driver monitoring device 2 described in the first embodiment. may be used by the monitoring device 6 to monitor the subject's condition. For example, restraint belt 7 is attached to bed 5 . FIG. 20 shows a connection relationship between a top view of the bed 5 and the monitoring device 6. As shown in FIG. A patient lying on a bed 5 is fixed with a restraint belt 7, and the monitoring device 6 may acquire the patient's body movement, breathing interval, ventilation volume, heart rate, tomographic image, etc. while lying down.
The operation of the monitoring device 6 is the same as the operation according to the processing flow shown in FIGS. 15-18.
According to the monitoring device described above, the condition of the person to be measured can be easily measured using the belt.

Note that electrode pads 12 equivalent to the suppression belt 7, curvature sensors 150, and the like are periodically arranged on the sheets of the bed 5 shown in FIG. You may make it monitor by the method similar to .
In this case, the sheet or mat of the bed 5 has a plurality of electrode pads 12 and a plurality of curvature sensors 150 . The monitoring device is then electrically connected to the electrode pads 12 and the curvature sensor 150 provided on the sheet or mat. The monitoring device then estimates the deformation of the sheet or mat based on the curvature data acquired via the curvature sensor 150 . For example, the change in the shape of the sheet or mat may be the change in the shape of the surface of the sheet or mat due to the change in the force applied to the sheet or mat when the subject moves his/her body. Alternatively, the change in the shape of the sheet or mat may be a minute change in the shape of the surface of the sheet or mat based on the subject's breathing or heartbeat. The monitoring device then determines the subject's condition based on the deformed shape of the sheets or mat. In addition, the monitoring device calculates state information of one or more of the tomographic image, heart rate, and ventilation state of the person to be measured based on the electrical signals obtained from the electrode pads 12 provided on the sheets and mats. The status information is used to determine whether the subject's status is normal or abnormal.

<Third Embodiment>
In the third embodiment, the electrode pads 12, the curvature sensor 150, and the like are periodically arranged on the sheet 4 shown in FIG. You may make it monitor by the method similar to .
In this case, the sheet 4 has multiple electrode pads 12 and multiple curvature sensors 150 . The monitoring device is electrically connected to the electrode pads 12 provided on the seat 4 and the curvature sensor 150 . The monitoring device then estimates the deformation of the seat 4 based on the curvature data acquired via the curvature sensor 150 . For example, the change in shape of the seat 4 may be a change in the shape of the surface of the backrest due to a change in the force with which the driver leans against the backrest. Alternatively, the change in the shape of the seat 4 may be a change in the shape of the surface of the backrest due to the action of the driver moving his/her body into and out of contact with the backrest. Alternatively, the change in the shape of the seat 4 may be a minute change in the shape of the backrest surface based on the driver's breathing or heartbeat. The monitoring device then determines the condition of the subject based on the deformed shape of the sheet 4 . In addition, the monitoring device calculates one or more of the tomographic image, heart rate, and ventilation state of the person to be measured based on the electrical signals obtained from the electrode pads 12 provided on the seat 4, and calculates the state information. The information is used to determine whether the subject's condition is normal or abnormal.

The seat belt 1, the seat 4, the bed 5, the sheets, the mat, etc. described in each of the above-described embodiments are examples of the body contact member.

The driver monitoring device 2 and the monitoring device 6 described above have a computer system inside. Each process described above is stored in a computer-readable recording medium in the form of a program, and the above process is performed by reading and executing this program by a computer. Here, the computer-readable recording medium refers to magnetic disks, magneto-optical disks, CD-ROMs, DVD-ROMs, semiconductor memories, and the like. Alternatively, the computer program may be distributed to a computer via a communication line, and the computer receiving the distribution may execute the program.

Further, the program may be for realizing part of the functions described above. Further, it may be a so-called difference file (difference program) that can realize the above-described functions in combination with a program already recorded in the computer system.

REFERENCE SIGNS LIST 1 seat belt 2 driver monitoring device 3 communication cable 4 seat 5 bed 6 monitoring device 7 suppression belt 11 measurement circuit 12 electrode pad 114 serial communication circuit 150 curvature sensor 156 amplifier 157 A/D converter 181...Signal conversion module

Claims (22)

A plurality of electrodes and a plurality of curvature sensors are connected to the electrodes and the curvature sensors in a member provided so as to correspond to the range of the body in contact with the spaced apart,
determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; determining whether the subject's condition is normal or abnormal using the condition information;
calculating state information of one or more of body movement, heart rate, and ventilation state of the person to be measured based on a signal obtained from one of the plurality of curvature sensors specified based on the shape; , a monitoring device that determines the condition of the subject using the condition information. a plurality of electrodes and a plurality of curvature sensors connected to the electrodes and the curvature sensors on a member provided so as to be spaced apart and corresponding to a region of the body;
determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; A monitoring device that determines whether the subject's condition is normal or abnormal using the condition information. A plurality of curvature sensors are spaced apart and connected to the curvature sensors in a seat belt, sheet, mat, or bed indicating member provided to correspond to an area of the body;
determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of body movement, heart rate, and ventilation state of the person to be measured based on a signal obtained from one of the plurality of curvature sensors specified based on the shape; and a monitoring device that determines the condition of the subject using the condition information. 4. The monitoring device according to claim 1, wherein the curvature sensor converts a potential difference caused by a difference in impedance of the strain gauges constituting the bridge circuit into a curvature of the member at the installation position of the strain gauge and outputs the curvature. . Claim 1 or claim 3 or claim 3, wherein state information of any one or a plurality of breathing interval, ventilation volume, heart rate, or changes thereof of said person to be measured is calculated based on the signal obtained from said curvature sensor. 5. A monitoring device according to any one of claims 4. 3. The method according to claim 1 or 2, wherein state information of one or a plurality of breathing interval, ventilation volume, heart rate, or changes thereof of said person to be measured is calculated based on the signals obtained from said electrodes. monitoring equipment. 7. The monitoring device according to claim 5, wherein the drowsiness or physical condition of the subject is determined based on the state information. The device according to any one of claims 1, 3 to 5, wherein the member estimates a contact range with the person to be measured, and drives the curvature sensor located in the contact range. A monitoring device as described. The state information is a tomographic image,
The member is electrically connected to the electrode of the member provided with a plurality of electrodes,
Based on the energization of the plurality of electrodes and the voltage signal generated between the electrodes, a tomographic image of the subject is generated in a range where the member contacts the subject, and based on the tomographic image 3. The monitoring device according to claim 1, wherein the condition of the person to be measured is determined by a recording unit that records the state information;
10. A monitoring device according to any one of claims 1 to 9, comprising: a display processing unit that displays the state information on a monitor;
11. A monitoring device according to any one of claims 1 to 10, comprising: 12. The monitoring device according to any one of claims 1 to 11, wherein a warning sensor is activated when it is determined that the subject's condition is abnormal. The monitoring device according to any one of claims 1 to 12, wherein control for outputting warning information or assisting driving operation of a driving object is performed based on the state information. The monitoring device according to any one of claims 1 , 2, and 4 to 13, wherein the member is one or a plurality of seat belts, sheets, mats, and beds. a monitoring device connected to the electrodes and the curvature sensors in a member provided to correspond to a region of the body where the plurality of electrodes and the plurality of curvature sensors are in spaced contact;
The monitoring device determines the shape of the person to be measured based on the signal obtained from the curvature sensor;
one or more of a tomographic image, a heart rate, and a ventilation state of the person to be measured based on electrical signals obtained from the electrodes specified based on the shape by the monitoring device among the plurality of electrodes; calculating information, and using the state information to determine whether the subject's state is normal or abnormal;
The monitoring device detects any one or more of body movement, heart rate, and ventilation state of the person to be measured based on the signal obtained from the curvature sensor specified based on the shape, among the plurality of curvature sensors. A monitoring method comprising calculating state information and determining the state of the subject using the state information. a monitoring device connected to the electrodes and the curvature sensors in a member provided such that the plurality of electrodes and the plurality of curvature sensors are spaced apart to correspond to a region of the body;
The monitoring device determines the shape of the person to be measured based on the signal obtained from the curvature sensor;
one or more of a tomographic image, a heart rate, and a ventilation state of the person to be measured based on electrical signals obtained from the electrodes specified based on the shape by the monitoring device among the plurality of electrodes; A monitoring method for calculating information and determining whether the subject's condition is normal or abnormal using the condition information. a monitoring device connected to said curvature sensors in a member indicative of any of a seat belt, a sheet, a mat, a bed having a plurality of spaced curvature sensors corresponding to areas of the body;
The monitoring device determines the shape of the person to be measured based on the signal obtained from the curvature sensor;
The monitoring device detects any one or more of body movement, heart rate, and ventilation state of the person to be measured based on the signal obtained from the curvature sensor specified based on the shape, among the plurality of curvature sensors. A monitoring method comprising calculating state information and determining the state of the subject using the state information. a computer of a monitoring device connected to the electrodes and the curvature sensors in a member provided to correspond to the range of the body where the plurality of electrodes and the plurality of curvature sensors are in contact with each other at intervals;
means for determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; means for determining whether the subject's condition is normal or abnormal using the condition information;
calculating state information of one or more of body movement, heart rate, and ventilation state of the person to be measured based on a signal obtained from one of the plurality of curvature sensors specified based on the shape; , means for determining the condition of the subject using the condition information;
A program characterized by functioning as a computer of a monitoring device connected to said electrodes and said curvature sensors on a member provided so that said electrodes and said curvature sensors are spaced apart and correspond to regions of the body;
means for determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; means for determining whether the subject's condition is normal or abnormal using the condition information;
A program characterized by functioning as a computer of a monitoring device connected to said curvature sensors in a member indicating any one of a seat belt, a sheet, a mat, a bed, in which a plurality of curvature sensors are spaced to correspond to a range of the body;
means for determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of body movement, heart rate, and ventilation state of the person to be measured based on a signal obtained from one of the plurality of curvature sensors specified based on the shape; , means for determining the condition of the subject using the condition information;
A program characterized by functioning as The electrodes and the curvature sensors in a member indicating any one of a seat belt, a sheet, a mat, and a bed provided so as to correspond to the range of the body where the plurality of electrodes and the plurality of curvature sensors are in contact with each other at intervals. connected to
determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; determining whether the subject's condition is normal or abnormal using the condition information;
calculating state information of one or more of body movement, heart rate, and ventilation state of the person to be measured based on a signal obtained from one of the plurality of curvature sensors specified based on the shape; , a monitoring device that determines the condition of the subject using the condition information. A plurality of electrodes and a plurality of curvature sensors are spaced apart and connected to the electrodes and the curvature sensors of a member indicating any one of a seat belt, a sheet, a mat, and a bed provided to correspond to the range of the body. is,
determining the shape of the person to be measured based on the signal obtained from the curvature sensor;
calculating state information of one or more of a tomographic image, a heart rate, and a ventilation state of the subject based on electrical signals obtained from the electrodes specified based on the shape among the plurality of electrodes; determining whether the subject's condition is normal or abnormal using the condition information.

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